Over the last decades, a lot of research has been carried out to bring forward many nature-inspired, optimization techniques. The behaviour pattern of natural phenomena such as evolution of species, working of neural networks etc. has been effectively simulated to perform various computing tasks.
SitoLIB is an open source library for human opinion formation based optimizer. It includes social impact theory based optimizer (SITO) and Durkheim's theory of social integration based optimizer(CODO). The goal is to develop an easy to understand, general-purpose software library which can be incorporated in application-specific systems. The present version of library includes the binary version and continuous(real-valued) version of the optimizer. Our binary implementation is based on theory of social impact given by [Latane, 1981] and pseudo code of the optimizer given by [Macas, 2008]. The continuous implementation referred as Continuous Opinion Dynamics Optimizer (CODO) is based on Durkheim's theory of social integration[Durkheim,1997] and pseudo code of the optimizer given by [Rishemjit, 2013].
So far, one variant of CODO and three different variants of SITO are implemented in the library for minimization of objection function which includes
• OSITO (original SITO algorithm),
• SSITOsum (Simplified SITO with SUM rule), SSITOmean Simplified SITO with MEAN rule) and
• GSITO (Galam-inspired SITO).

These variants have been effectively brought into use in different applications such as feature subset selection using UCI machine learning repository datasets [Macas, 2007], itongue optimization [Bhondekar, 2011], and enhancing e-nose performance [R. Kaur, 2012]. CODO has been used for optimization of complex mathematical functions[R. Kaur, 2013]
The source code is available from the website sitolib.org. It can be compiled on Microsoft Windows. The usage(Sito Library.pdf) and example usage script(sitodriver.m) is included in the rar file.

Changes to previous version:

A new variant 'Continuous Opinion Dynamics Optimizer (CODO)' has been implemented in this version.
Minor changes in implementation of objective function.